In [14]:
G = mu.ff_graph(mesh)
print(mesh.n_faces(), G.number_of_nodes())
nx.draw(G, node_size=40, pos=nx.spring_layout(G, seed=2))
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A collection of python utilities for mesh processing.
colormap_vertex_color: assign vertex color to visualize a scalar field defined on mesh.isocurve: extract isocurves on a scalar field defined on a manifold triangular mesh.mesh_cut: cut a mesh along a vertex chain.mesh_split: split a mesh by inserting new vertices defined on mesh edges.sphere_cvt: iteratively approximate centroidal Voronoi tessellation (CVT) on the unit sphere (kind of uniform sampling).split_connected_components: split connected components.write_obj_lines: write polyline as a Wavefront .obj file, which can be open with MeshLab.pyisocurve (C++ based): almost the same as isocurve above.pygeodesic (C++ based): exact geodesic for triangular meshes.import numpy as np
import openmesh as om
import meshplot as mp
# mp.offline()
import networkx as nx
import sys
sys.path.append('../../')
import MeshUtility as mu
verts, faces = mu.sphere_cvt(100, iters=100)
100/100
p = mp.plot(verts, faces, return_plot=True)
p.save("../data/sphere_cvt.html")
Plot saved to file ../data/sphere_cvt.html.
p = mp.plot(verts, c=verts, shading={"point_size": 0.3}, return_plot=True)
p.save("../data/sphere_cvt_v.html")
Plot saved to file ../data/sphere_cvt_v.html.
mesh = om.TriMesh(verts, faces)
field = verts[:, 1]
isocurve = mu.IsoCurve(verts, faces, field)
pts, on_edges, ratios, isocurve_indices = isocurve.extract(0.5)
p = mp.plot(verts, faces, c=field, return_plot=True)
edges = []
for line in isocurve_indices:
edges.extend([[line[i], line[i+1]] for i in range(len(line)-1)])
edges = np.array(edges, 'i')
p.add_edges(pts, edges, shading={"line_color": "red"})
p.save("../data/isocurve.html")
Plot saved to file ../data/isocurve.html.
mesh_split, curve_idx = mu.split_mesh(mesh.points(),
mesh.face_vertex_indices(),
on_edges, ratios)
np.random.seed(5)
d = mp.subplot(verts, faces, c=np.random.rand(*faces.shape), s=[1, 2, 0])
np.random.seed(5)
mp.subplot(mesh_split.points(), mesh_split.face_vertex_indices(), c=np.random.rand(mesh_split.n_faces(), 3), s=[1, 2, 1], data=d)
# add_edges(pts, edges, shading={"line_color": "red"}); # how to add edges in subplot?
p.save("../data/split.html")
Plot saved to file ../data/split.html.
curve_idx_ring = curve_idx + [curve_idx[0]]
curve = [curve_idx_ring[v] for v in isocurve_indices[0]]
mesh_cut, curve_idx = mu.cut_along_curve(mesh_split.points(),
mesh_split.face_vertex_indices(),
curve)
parts = mu.split_connected_components(mesh_cut.points(),
mesh_cut.face_vertex_indices())
n = len(parts)
d = mp.subplot(parts[0].points(), parts[0].face_vertex_indices(), s=[1, n, 0])
for i in range(1, n):
mp.subplot(parts[i].points(), parts[i].face_vertex_indices(), s=[1, n, i], data=d)
p.save("../data/cut.html")
Plot saved to file ../data/cut.html.
u, v = 0, 20
path_edge, path_ratio = mu.pygeodesic.find_path(verts, faces, u, v)
pts0 = verts[path_edge[:,0]]
pts1 = verts[path_edge[:,1]]
pts = np.multiply(pts0, 1.-path_ratio[:, np.newaxis]) + \
np.multiply(pts1, path_ratio[:, np.newaxis])
p = mp.plot(verts, faces, return_plot=True)
edges = [[i, i+1] for i in range(pts.shape[0]-1)]
edges = np.array(edges, 'i')
p.add_edges(pts, edges, shading={"line_color": "red"})
p.save("../data/geodesic_path.html")
Plot saved to file ../data/geodesic_path.html.
mesh_split, source = mu.split_mesh(verts, faces,
path_edge, path_ratio)
# compute geodesic distance field
field = mu.pygeodesic.distance_field(mesh_split.points(),
mesh_split.face_vertex_indices(),
source, 0.05)
mp.plot(mesh_split.points(), mesh_split.face_vertex_indices(), c=field)
p.save("../data/geodesic_field.html")
Plot saved to file ../data/geodesic_field.html.
G = mu.ff_graph(mesh)
print(mesh.n_faces(), G.number_of_nodes())
nx.draw(G, node_size=40, pos=nx.spring_layout(G, seed=2))
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G = mu.ff_graph(mesh_cut)
print(mesh_cut.n_faces(), G.number_of_nodes())
nx.draw(G, node_size=40, pos=nx.spring_layout(G, seed=11))
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